The Association Between e-Health Literacy and Willingness to Deprescribe Among Patients with Chronic Diseases: A Cross-Sectional Study from Jordan

Abstract

Background:

Deprescribing refers to the partnered discontinuation of chronic medications to limit the negative impacts of polypharmacy. Polymedicated patients play a key role in the success of deprescribing efforts. eHealth literacy reflects patients' ability to appraise electronically available health-related information to make informed health care decisions, which partly reflect their desire to deprescribe.

Objectives:

The current study aimed to explore the relationship between eHealth literacy and willingness to deprescribe among patients with chronic diseases. Additionally, the predictors of willingness to deprescribe were examined.

Materials and Methods:

This cross-sectional study was conducted among adult patients with chronic diseases in Jordan. An online questionnaire comprising two validated tools, namely the Electronic Health Literacy Scale (eHEALS) and the Revised Patients' Attitudes Toward Deprescribing (rPATD) Questionnaire, was used for data collection. The questionnaire targeted adult patients with chronic medical conditions in Jordan and was posted to social media portals, following a convenience sampling technique.

Results:

A total of 719 responses were recorded and included in the final analysis. Participants with higher levels of eHealth literacy were more willing to get their medications deprescribed, as indicated by the perceived use of unneeded medications (p = 0.042). Meanwhile, participants with low levels of eHealth literacy were more likely to report fear of missing out on the potential benefits of deprescribed medications (p = 0.003). Other items that were commonly agreed upon by both the low and high eHealth literacy groups, respectively, included desire for dose reduction (p < 0.001, p < 0.001), belief in the lack of effectiveness of some prescribed medications (p < 0.001, p < 0.001), and fear of precipitating side effects (p = 0.001, p = 0.007).

Conclusions:

The present study highlighted the relationship between eHealth literacy and a number of items reflecting willingness to deprescribe, and these indicators can be used to guide future deprescribing efforts among eligible patients.

Introduction

Over the past few years, chronic diseases have dominated as leading causes of death around the world, regardless of factors such as income level.¹ Globally, the aging population is growing, along with an expected parallel increase in the coexistence of chronic diseases.² In addition to the risk of all-cause mortality, chronic diseases pose a great burden on people's overall health and health care costs.³ To better highlight this, one in three adults worldwide suffers from more than one chronic disease, which dictates the prescribing of multiple medications to treat their different diseases.⁴

In addition to the associated direct costs, polypharmacy is a well-known risk factor for toxicities and drug interactions.⁵ Furthermore, the triad of aging, chronic diseases/frailty, and polypharmacy enhances the potential of developing associated serious consequences, including drug–drug interactions, drug–disease interactions, and adverse drug events.⁶

To limit such risks, deprescribing, which is defined as the supervised cessation of inappropriate medications, has been suggested as a method of reducing the problems associated with polypharmacy.^6,7 However, willingness to deprescribe among polymedicated patients is affected by multiple factors.^5,8 To mention a few, prescriber's support and perceived discontinuation benefits have been identified as major enablers of deprescribing.⁵

Meanwhile, the reported potential barriers to deprescribing include elderly patients' inability to comprehend health-related information and use this information appropriately to communicate individual preferences to prescribers, otherwise referred to as low health literacy.⁸ However, there is a lack of published literature related to the association between willingness to deprescribe and eHealth literacy, a contemporary term which refers to patients' ability to access relevant online resources to find information pertaining to their health and apply the retrieved knowledge to make informed health-related decisions.⁹

Thus, the aim of this study was to assess the relationship between willingness (readiness) to deprescribe and eHealth literacy among patients with chronic diseases. Additionally, the present study aimed to explore the potential factors that affect the association between willingness to deprescribe and eHealth literacy among people with chronic diseases.

Methodology

A cross-sectional survey was conducted among adult patients with chronic diseases in Jordan. An online self-administered questionnaire was used to collect data between February and April 2021. The questionnaire comprised two validated tools, namely the Electronic Health Literacy Scale (eHEALS) and the Revised Patients' Attitudes Toward Deprescribing (rPATD) questionnaire.^7,10 The participants were informed that clicking the “proceed” button would implicitly indicate providing informed consent to participate in the study. Ethics approval for conducting this study was obtained from the Institutional Review Board (IRB) of King Abdullah University Hospital (reference number 19/119/2018).

SAMPLING

The questionnaire was posted to social media platforms following a convenience sampling technique and targeted adult patients with chronic medical conditions in Jordan. The researchers and research assistants identified active pages and groups on Facebook and WhatsApp where health care professionals primarily discussed topics related to chronic disease management (e.g., diabetes and hypertension) or where patients shared their experiences and concerns regarding their chronic conditions. A reminder to take part in the study was posted every 48 h during the first week and on a weekly basis for the remaining 7 weeks.

To minimize response bias and avoid multiple responses from the same participant, the online survey did not allow for multiple responses from the same IP address. The survey also included items related to country and city of residence to exclude potential responses from outside of Jordan. Moreover, the participation information sheet included with the survey assured the participants that all responses would be kept anonymous and that no personal information was required.

The minimum sample size was calculated using the online sample size calculator Rao Soft^®. The estimated number of adults (i.e., 18 years of age or over) in Jordan is 3,500,000. With a margin of error of 4% and a confidence interval of 95%, the sample size generated by the software was 601 adults.

SURVEY INSTRUMENTS

eHEALS was developed by Norman and Skinner¹⁰ to address the need for e-Health literacy assessment to explore the consumer e-Health-related skills employed in clinical decision making. eHEALS is an eight-item instrument that measures respondents' perceived skills at acquiring, evaluating, and applying electronic health information to health problems.¹¹ The eHEALS items are scored using a 5-point Likert scale with response options ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The total possible eHEALS score ranges from 8 to 40, with higher scores indicating higher levels of self-perceived e-Health literacy.

The psychometric properties of the eHEALS were originally evaluated by Norman and Skinner among a young population group. The psychometric analysis revealed that eHEALS is a tight-fitting scale with a Cronbach's alpha of 0.88, and the principal components analysis produced a single-factor solution with factor loadings ranging from 0.60 to 0.84.¹⁰

The rPATD questionnaire was developed by Reeve et al.⁷ to assess patients' attitudes and beliefs toward deprescribing. The rPATD questions are scored on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The questionnaire measures four constructs: (1) burden (i.e., the burden of the used medications), (2) appropriateness (i.e., patients' perceived benefits and harms of the medications they are taking), (3) concerns about stopping (i.e., patients' concerns about stopping their medications), and (4) involvement (i.e., patients' knowledge and involvement in decision making about their medication therapy).

The questionnaire also included two questions to assess patients' overall satisfaction with their current medications and willingness to stop one or more of their medications if advised to do so by their physician. The rPATD has been evidenced to be valid and reliable and has been translated and cross-culturally adapted into different languages.^7,12

In the present study, the Arabic versions of both the eHEALS and the rPATD were used to ensure that the participants were able to fully comprehend the questionnaires, since Arabic is the official language in Jordan. Previous studies have translated and cross-culturally adapted the eHEALS and rPATD into Arabic and reported both questionnaires to be valid and reliable.^13,14

DATA ANALYSES

Data analyses were performed using the IBM SPSS^® (Statistical Package for the Social Sciences, Armonk, NY) program version 24. The median total eHEALS score was used to dichotomize the respondents into two groups (i.e., median split). Participants with a score below the median score were labeled as “low eHEALS,” whereas participants with a score above the median score were labeled as “high eHEALS”¹¹. Descriptive statistical analyses were used to describe the respondents' sociodemographic characteristics of high and low e-Health literacy groups. Cronbach's alpha coefficients were used to assess the internal consistency of the Arabic eHEALS and rPATD questionnaire. Moreover, statistically significant associations between the rPATD items and e-Health literacy were tested using unpaired t-test.

Furthermore, binary logistic regressions were performed to identify the predictors of willingness to deprescribe for each of the e-Health literacy groups independently. Similar to a previous study by Scott et al.,¹⁵ the appropriateness question, “I would like to try stopping one of my medicines to see how I feel without it,” was set as the primary outcome for the regression to identify patients' willingness to deprescribe. The participants' responses to all of the rPATD items were dichotomized (0 for strongly disagree, disagree, and neutral, and 1 for strongly agree and agree) to perform the binary logistic regression.

To ensure sufficient variability, the rPATD items were cross-tabulated with the primary outcome (“I would like to try stopping one of my medicines to see how I feel without it”), and items with insufficient variability (<5% distribution) were excluded. The statistical significance level was set at p < 0.05.

Results

A total of 2,679 attempts to fill out the online survey were recorded. A total of 814 participants completed the survey (response rate = 30.4%). Responses from participants residing outside of Jordan were excluded (n = 95), resulting in a total of 719 responses included in the statistical analyses. Detailed demographic characteristics of the sample are presented in Table 1. The respondents in both the low and high e-Health literacy groups were almost equally distributed in terms of gender, with 48.7% of the sample being female and 51.3% being male. Respondents who identified themselves as health care professionals had higher eHealth literacy scores (31.4 ± 5.26) than did non-health care professionals (29.2 ± 5.22; p = 0.021).

Table 1.

Baseline Demographic Characteristics of Study Participants

CHARACTERISTICS	n (%)	E-HEALTH LITERACY SCORE MEAN (SD)	p	LOW E-HEALTH LITERACY GROUP ( N = 342) n (%)	HIGH E-HEALTH LITERACY GROUP ( N = 377) n (%)	p
Gender
Male	369 (51.3)	29.5 (5.15)	0.714	169 (45.8)	200 (54.2)	0.333
Female	350 (48.7)	29.6 (5.4)	0.714	173 (49.4)	177 (50.6)	0.333
Age
18–24	41 (5.7)	28.8 (6.05)	0.074	22 (53.7)	19 (46.3)	0.011
25–34	104 (14.5)	30.3 (4.46)		45 (43.3)	59 (56.7)
35–44	143 (19.9)	30.9 (4.58)		47 (32.9)	96 (67.1)
45–55	206 (28.7)	29.8 (5.01)		102 (49.5)	104 (50.5)
More than 55	225 (31.3)	28.2 (5.81)		126 (56)	99 (44)
Region
North	148 (20.6)	29.7 (5.81)	0.206	72 (48.6)	76 (51.4)	0.794
Central	540 (75.1)	29.5 (5.14)		252 (46.7)	288 (53.3)
South	31 (4.3)	29.2 (5.19)		18 (58.1)	13(41.9)
Monthly income
Less than 250	125 (17.4)	29.4 (5.48)	0.088	64 (51.2)	61 (48.8)	0.024
250–499	213 (29.6)	29.4 (5.38)		108(50.7)	105(49.3)
500–999	233 (32.4)	29.5 (4.97)		109 (46.8)	124 (53.2)
1000–1499	71 (9.9)	29.0 (5.39)		35 (49.3)	36 (50.7)
More than 1500	77 (10.7)	30.7 (5.47)		26 (33.8)	51 (66.2)
Education
Up to secondary level	182 (25.3)	28.9 (5.18)	0.377	98 (53.8)	84 (46.2)	0.019
Undergraduate level	443 (61.6)	29.6 (5.41)		207 (46.7)	236 (53.3)
Postgraduate level	94 (13.1)	30.6 (4.67)		37 (39.4)	57 (60.6)
Employment
Employed	311 (43.3)	30.1 (5.20)	0.489	129 (49.6)	182 (58.5)	0.370
Unemployed	246 (34.2)	29.4 (5.47)		122(49.6)	124 (50.4)
Retired	162 (22.5)	28.6 (5.02)		91 (56.2)	71 (43.8)
Health care profession
Yes	99 (13.8)	31.4 (5.26)	0.021	33 (33.3)	66 (66.7)	0.002
No	620 (86.2)	29.2 (5.22)	0.021	309 (49.8)	311 (50.2)	0.002
Smoker
Yes	192 (26.7)	29.8 (5.37)	0.575	82 (42.7)	110 (57.3)	0.129
No	527 (73.3)	29.4 (5.25)	0.575	260 (49.3%)	267 (50.7%)	0.129

	ALL PARTICIPANTS MEAN (SD)	LOW E-HEALTH LITERACY GROUP MEAN (SD)	HIGH E-HEALTH LITERACY GROUP MEAN (SD)	p
Average number of cigarettes/days	21.69 (12.58)	22.27 (12.9)	21.26 (12.37)	0.584
Average number of medications	3.31 (2.46)	3.54 (2.36)	3.1 (2.53)	0.018
Chronic conditions	1.8 (3.80)	2.01 (3.32)	1.61 (3.64)	0.002

eHEALS: Electronic Health Literacy Scale; SD, standard deviation.

Moreover, individuals in the low eHealth literacy group were more likely to be of older ages (p = 0.011) and to have lower income (p = 0.024) than were participants in the high e-Health literacy group. They were also more likely to report lower education levels (p = 0.019), have a higher average number of prescribed medications (p = 0.018), and suffer from a higher number of chronic diseases (p = 0.002). On the other hand, participants in the high e-Health literacy group were more likely to have a health care-related profession (p = 0.002).

The eHEALS was found to have excellent reliability, as indicated by the calculated Cronbach's alpha of 0.915. The mean eHEALS score among the participants was 29.52 (±5.28) (ranging from 8 to 40), whereas the mean scores for the separate items ranged from 3.77 (±0.80) to 3.58 (±0.89). The mean scores for the eHEALS items are presented in Table 2.

Table 2.

eHEALS Items' Mean Scores

EHEALS QUESTIONS	MEAN ± SD
I know what health resources are available on the Internet	3.66 ± 0.818
I know where to find helpful health resources on the Internet	3.69 ± 0.85
I know how to find helpful health resources on the Internet	3.72 ± 0.83
I know how to use the Internet to answer my health questions	3.77 ± 0.80
I know how to use the health information I find on the Internet to help me	3.74 ± 0.76
I have the skills I need to evaluate the health resources I find on the Internet	3.58 ± 0.89
I can tell high-quality health resources from low-quality health resources on the Internet	3.67 ± 0.86
I feel confident in using information from the Internet to make health decisions	3.69 ± 0.84

The rPATD questionnaire showed good reliability, with a calculated Cronbach's alpha of 0.831. A general overview of the respondents' responses to the rPATD items is presented in Table 3. Almost all of the respondents (95%) in the high e-Health literacy group reported knowing exactly what medicines they were taking and/or keeping an updated list of their used medications. Moreover, the majority of the participants in the same group (91.5%) reported good understanding of the reasons behind the initiation of their prescribed medications. Additionally, 84.9% of the high eHealth literacy group participants reported overall satisfaction with their prescribed medications, as compared with a 78.1% satisfaction rate in the low eHealth literacy group (p < 0.001).

Table 3.

Association Between rPATD Items and e-Health Literacy Groups

ITEM	% OF AGREEMENT (STRONGLY AGREE/AGREE) IN HIGH EHEALS	% OF AGREEMENT (STRONGLY AGREE/AGREE) IN LOW EHEALS	MEAN SCORES IN HIGH HEALTH LITERACY GROUP	MEAN SCORES IN LOW HEALTH LITERACY GROUP	p
I spend a lot of money on my medicines	50.9	48.5	3.37 ± 1.09	3.38 ± 1.09	0.969
Taking my medicines every day is very inconvenient	63.9	65.5	3.63 ± 1.14	3.66 ± 1.10	0.727
I feel that I am taking a large number of medicines	45.1	53.8	3.13 ± 1.21	3.38 ± 1.19	0.006
I feel that my medicines are a burden to me	49.6	54.1	3.27 ± 1.14	3.43 ± 1.09	0.057
Sometimes I think I take too many medicines	50.9	57	3.23 ± 1.19	3.43 ± 1.14	0.021
I feel that I may be taking one or more medicines that I no longer need	19.4	24.9	2.48 ± 1.04	2.66 ± 1.03	0.016
I would like my doctor to reduce the dose of one or more of my medicines	42.1	45.9	3.08 ± 1.04	3.24 ± 1.07	0.057
I would like to try stopping one of my medicines to see how I feel without it	44	47.7	3.06 ± 1.21	3.17 ± 1.19	0.204
I think one or more of my medicines may not be working	21.8	31	2.55 ± 1.03	2.8 ± 1.06	0.001
I believe one or more of my medicines may be currently giving me side effects	51.2	54.7	2.55 ± 1.03	2.80 ± 1.06	0.224
I would be reluctant to stop a medicine that I had been taking for a long time	71.6	71.1	3.68 ± 1.05	3.75 ± 0.98	0.379
If one of my medicines was stopped, I would be worried about missing out on future benefits	62.9	60.8	3.51 ± 1.09	3.49 ± 1.04	0.769
I get stressed whenever changes are made to my medicines	51.2	51.5	3.28 ± 1.05	3.39 ± 0.98	0.137
If my doctor recommended stopping a medicine, I would feel that he/she was giving up on me	14.9	17.5	2.39 ± 0.96	2.49 ± 0.96	0.136
I have had a bad experience when stopping a medicine before	39.8	40.4	3.01 ± 1.21	3.08 ± 1.12	0.451
I have a good understanding of the reasons I was prescribed each of my medicines	91.5	84.5	4.27 ± 0.76	4.01 ± 0.81	<0.001
I know exactly what medicines I am currently taking, and/or I keep an up-to-date list of my medicines	95	87.1	4.31 ± 0.66	4.09 ± 0.73	<0.001
I like to know as much as possible about my medicines	89.9	88.9	4.25 ± 0.71	4.16 ± 0.69	0.102
I like to be involved in making decisions about my medicines with my doctors	88.6	82.5	4.19 ± 0.77	4.06 ± 0.80	0.018
I always ask my doctor, pharmacist or other health care professional if there is something I do not understand about my medicines	92.8	88	4.31 ± 0.70	4.14 ± 0.72	0.001
Overall, I am satisfied with my current medicines	84.9	78.1	4.05 ± 0.78	3.82 ± 0.75	<0.001

rPADT, Revised Patients' Attitudes Toward Deprescribing score (1: strongly disagree, 2: disagree, 3: neither agree nor disagree, 4: agree, 5: strongly agree).

A comparison between the participants' rPATD responses based on their eHealth literacy status (Table 3) showed that participants with low eHealth literacy were more likely to report reluctance toward the necessity of their prescribed medications (p = 0.016) and hesitance about the beneficial role of their prescribed medications (p = 0.001). Compared with participants with low eHealth literacy, participants in the high eHealth literacy group were more likely to report feeling comfortable with the number of medications taken as “neither being large” (p < 0.006) nor “way more than needed” (p = 0.021). In addition, they were more likely to report that they understood why their medications were prescribed and to keep track of an updated list of their used medications (p < 0.001, p < 0.001, respectively).

Also, they were more likely to get involved in making decisions related to their prescribed medications (p = 0.018). Moreover, participants in the high eHealth literacy group were more likely to consult health care providers to solve any uncertainties related to their prescribed medications (p < 0.001), and they were more likely to report satisfaction with their current medications (p < 0.001).

Table 4 highlights the model-derived difference in information perception related to prescribed medications and a number of rPATD items predicting participants' desire to try stopping a medicine in both groups. Participants in the high e-Health literacy group were significantly more willing to have some of their chronic medications deprescribed, as indicated by the perceived use of unneeded medications (p = 0.042). Meanwhile, participants in the low e-Health literacy group were more likely to report fear of missing out on the potential benefits of stopped medications (p = 0.003).

Table 4.

rPATD Items Predicting High and Low eHEALS Desire to Try Stopping a Medicine

ITEM	OR (95% CI)	p
Low eHEALS group
I would like my doctor to reduce the dose of one or more of my medicines	0.150 (0.077–0.291)	<0.001
I think one or more of my medicines may not be working	0.118 (0.062–0.225)	<0.001
I believe one or more of my medicines may be currently giving me side effects	0.349 (0.186–0.654)	0.001
If one of my medicines was stopped, I would be worried about missing out on future benefits	2.584 (1.37–4.876)	<0.001
High e-HEALS group
I feel that I may be taking one or more medicines that I no longer need	0.495 (0.215–0.976)	0.042
I would like my doctor to reduce the dose of one or more of my medicines	0.242 (0.138–0.424)	<0.001
I think one or more of my medicines may not be working	0.16 (0.084–0.304)	<0.001
I believe one or more of my medicines may be currently giving me side effects	0.472 (0.273–0.817)	0.007

CI, confidence interval; OR, odds ratio.

Other items that were commonly agreed upon among the respondents in both the low and high eHealth literacy groups (respectively) included the desire for dose reduction (p < 0.001, p < 0.001), belief in the lack of effectiveness of some prescribed medications (p < 0.001, p < 0.001), and fear of precipitating side effects (p = 0.001, p = 0.007). It is worth noting that there were no statistically significant associations between the participants' sociodemographic characteristics and their responses to the rPATD items.

Discussion

Deprescribing is the coordinated partnership between caregivers and patients with the ultimate goal of reducing medication burden while preserving patients' best interest. The current study aimed to identify which, if any, of the rPATD items can be used to identify patients who are willing to have a medication deprescribed in light of their e-Health literacy score. The present study reported a statistically significant relationship between eHEALS score and 9 of the rPATD items, whereby these items significantly predicted willingness to deprescribe among participants in both the low and high e-Health literacy groups.

The present study identified three major predictors of willingness to deprescribe, namely desire for dose reduction, perception of the necessity of prescribed medications, and side effect potential. The first two diagnostic indicators have previously been identified by Scott et al.¹⁵ as predictors of the desire to deprescribe among patients. However, the item related to side effect potential was not highlighted in their research, whereas perception related to the number of used medications was pointed out as an additional diagnostic indicator.¹⁵ On the other hand, a couple of other studies have reported fear of side effects as a potential reason for wanting to stop medications among polypharmacy patients.^5,8

In assessing the potential usability of baseline characteristics as predictors for willingness to deprescribe, the current study failed to underpin statistically significant associations between any of the measured baseline characteristics and willingness to deprescribe based on the rPATD items. This finding is congruent with the results of another study in which the demographic characteristics of patients were not found to predict their willingness to deprescribe.¹⁶

Higher e-Health literacy scores were positively correlated with willingness to get involved in the health care decision-making process. This finding is comparable to the finding reported by a study which investigated the correlations between health literacy capabilities in community-dwelling older patients and attitudes toward deprescribing.⁸

As compared with the low e-Health literacy group participants, the participants in the high eHealth literacy group were more willing to consult health care professionals and reported better overall satisfaction with prescribed medications. Both of these factors are expected to increase patients' willingness to engage in active conversations with health care providers to discuss deprescribing their medications. This association between higher health literacy scores and the key elements of proactive deprescribing was reported by Gillespie et al.⁸

The perceived high knowledge about prescribed medications reported by the low e-Health literacy group seemed contradictory to their responses indicating their lack of desire to deprescribe or have an active role in their health care decisions. This may be due to the low e-Health literacy group participants having a false subjective belief that they possess sufficient knowledge about their medications, when in fact they may have suboptimal knowledge that impacts their desire to deprescribe. However, there is a lack of comparable studies in the literature to refute or confirm such assumptions.

With regards to the burden factor, participants who had lower eHealth literacy scores were more likely to report their prescribed medications as being a burden. They were also more likely to question the appropriateness of prescribed medications. These findings are consistent with previous study findings, which have evidenced that low eHealth literacy contributes to poor overall knowledge about medications and poor ability to comprehend the appropriateness of prescribed medications.⁸

STRENGTHS AND LIMITATIONS

To the best of the authors' knowledge, this was the first national study of its kind to assess the relationship between eHealth literacy and willingness to deprescribe among Jordanian patients with chronic diseases. Validated multidimensional questionnaires among a relatively large number of patients were used, which also adds to the strength of the current research.

One limitation to the current study is that the use of online sampling and self-reporting may have limited certain eligible populations from accessing the questionnaires and participating in the study. However, the large number of participants should have compensated for any potential deficiencies related to this aspect. Statistically, our sample is fairly representative of the Jordanian population, given the large number of recorded responses. However, the reliance on online sampling through social media portals and electronic devices (e.g., computers and cellphones) may have led to selection bias in favor of high e-Health literacy participants, which may limit the generalizability of our findings.

Another limitation to this study is the potential of social desirability bias, whereby some respondents may have provided certain responses based on these responses being viewed favorably by others. Moreover, given the limited number of studies addressing the relationship between eHealth literacy and willingness to deprescribe, it was difficult to compare our findings with those of previous studies.

Furthermore, the participants' responses to the rPATD items were changed from 5-point Likert scale responses to binary values, whereby neutral responses to the rPATD items were grouped with “disagree” responses. This increased the number of “disagree” responses and hence may have resulted in bias. However, this approach was convenient for performing the binary logistic regression and has previously been used in other studies of similar nature.¹⁵

FUTURE DIRECTION

The indicators of willingness to deprescribe, identified in the present study, can serve as a framework to facilitate screening patients for willingness to participate in deprescribing interventions. There is a need for further investigation of the attitudinal predictors of successful deprescribing to ensure a clinical equipoise of medication cessation without precipitating counteracting symptoms of withdrawal or disease reactivation.

Conclusion

Deprescribing is based on a partnership involving both caregivers and patients. External characteristics are poor predictors of willingness or desire to get involved in medication discontinuation. Thus, it is important to gain a better understanding of the behavioral and attitudinal predictors of willingness to deprescribe. The present study highlighted the relationship between eHealth literacy and a number of items reflecting willingness to deprescribe, and these indicators can be used to guide future deprescribing efforts among eligible patients.

Footnotes

Authors' Contributions

R.A.K.: Conceptualization, data curation, investigation, methodology, project administration, resources, software, supervision, writing—original draft, writing—review & editing. M.B.N.: Conceptualization, methodology, data curation, formal analysis, software, investigation, methodology, project administration, writing—original draft, writing—review & editing. R.M.A.: Conceptualization, investigation, methodology, project administration, writing—review & editing. R.K.: Conceptualization, investigation, methodology, approvals acquisition, project administration, writing—review & editing. S.A.-A.: Conceptualization, investigation, project administration, writing—review & editing.

Acknowledgment

The authors would like to acknowledge the Institutional Review Board at King Abdullah University Hospital for approving the present study.

Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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